AI Governance

A field guide to AI governance as an operational practice — not compliance theater, not a checklist of ethical principles, but the daily work of running AI systems with the rigor organizations already apply to financial and industrial systems where the consequences of failure are real.

Drawn from conversations with engineers, compliance officers, finance partners, and platform leads, this book lays out the five technical pillars that have emerged as a rough industry consensus — runtime guardrails, observability, AI FinOps, policy as code, and provider-agnostic routing — and a pragmatic roadmap for organizations starting from scratch.

Short on purpose. Written in the middle of the work it describes.